activity
20162023
most citedReplication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs

320 citations · 364 across the 7 of their papers we have counts for

collaborators

8 papers

stat.ME2023

Inventing a coin-flip classifier: Accounting for multiplicity in machine learning benchmark performance

Kajsa Møllersen, Einar Holsbø

State-of-the-art (SOTA) performance refers to the highest performance achieved by some model on a test sample, preferably under controlled conditions such as public data (reproduci…

eess.IV2022★ 1 cited

A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images

Nikita Shvetsov, Morten Grønnesby, Edvard Pedersen +5

Increased levels of tumor infiltrating lymphocytes (TILs) in cancer tissue indicate favourable outcomes in many types of cancer. Manual quantification of immune cells is inaccurate…

cs.CV2021

Instance Segmentation of Microscopic Foraminifera

Thomas Haugland Johansen, Steffen Aagaard Sørensen, Kajsa Møllersen +1

Foraminifera are single-celled marine organisms that construct shells that remain as fossils in the marine sediments. Classifying and counting these fossils are important in e.g. p…

cs.CV2018★ 320 cited

Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs

Mike Voets, Kajsa Møllersen, Lars Ailo Bongo

Replication studies are essential for validation of new methods, and are crucial to maintain the high standards of scientific publications, and to use the results in practice. We h…

stat.ML2018★ 3 cited

A bag-to-class divergence approach to multiple-instance learning

Kajsa Møllersen, Jon Yngve Hardeberg, Fred Godtliebsen

In multi-instance (MI) learning, each object (bag) consists of multiple feature vectors (instances), and is most commonly regarded as a set of points in a multidimensional space. A…

stat.ML2018★ 15 cited

Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images

Kajsa Møllersen, Maciel Zortea, Thomas R. Schopf +2

Melanoma is the deadliest form of skin cancer. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classif…

stat.ML2016★ 7 cited

On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering

Kajsa Møllersen, Subhra S. Dhar, Fred Godtliebsen

Hybrid clustering combines partitional and hierarchical clustering for computational effectiveness and versatility in cluster shape. In such clustering, a dissimilarity measure pla…

physics.med-ph2016★ 18 cited

Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images

Kajsa Møllersen, Herbert Kirchesch, Maciel Zortea +3

Commercially available clinical decision support systems (CDSSs) for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert k…